There is a wide array of technologies directed to in vivo and ex vivo imaging of mammals—for example, bioluminescence, fluorescence, X-ray computed tomography, and multimodal imaging technologies. In vivo imaging of small mammals and ex vivo imaging of samples from small mammals is performed by a large community of investigators in various fields, e.g., oncology, infectious disease, and drug discovery.
Micro computed tomography (hereafter, “microCT”) imaging, is an x-ray-based technology that can image tissues, organs, and non-organic structures with an extremely high resolution. MicroCT has evolved quickly, requiring low dose scanning and fast imaging protocols to facilitate multi-modal applications and enable longitudinal experimental models. Similarly, nano-computed tomography (nanoCT) systems designed for high-resolution imaging of ex vivo samples are also now used. Multi-modal imaging involves the fusion of images obtained in different ways, for example, by combining fluorescence molecular tomography (FMT), PET, MRI, CT, and/or SPECT imaging data.
Conventional image analysis applications and/or imaging systems typically allow for visualization, analysis, processing, segmentation, registration and measurement of biomedical images. These applications and systems also provide volume rendering tools (e.g., volumetric compositing, depth shading, gradient shading, maximum intensity projection, summed voxel projection, signal projection); manipulation functions (e.g., to define areas of structures of interest, delete unwanted objects, edit images and object maps); and measurement functions (e.g., calculation of number of surface voxels, number of exposed faces, planar area of a region, estimated surface area of a region).
Acquisition of animal images can be time consuming, and rapid analysis of the acquired images is key to the efficiency of the process. Three dimensional (3D) imaging software, including microCT image analysis, enables extraction of structural, biological, and anatomical attributes from images, such as thickness, porosity, anisotropy, and other measures, of organs of interest, such as bones. Due to the anatomical contrast and high spatial resolution provided by microCT systems, they are widely used for studying skeletal bone formation, structure, and diseases. Automation of such analyses improves throughput, accuracy, and efficacy. In classical bone analysis approaches, researchers were required to visually and manually quantify the structural attributes of bones using printed images produced by the microCT platform. While some image analysis systems have been developed for computer-aided bone analysis, the digital workflows offered by bone analysis software still require considerable manual input and interaction from users and researchers. For example, such manual feedback is currently required to obtain stereological measures of cortical and trabecular bone compartments, e.g., manual selection of discrete 2-D slices of a 3-D bone image from which averaged thicknesses or other properties are determined.
Some conventional image analysis systems focus on locating the principal axes of the bones to extract the direction of 2-D slices of the bone. But principal axes do not carry detailed shape and directional information. Principal axes represent the major and minor directional axes of a bone, as shown in FIG. 1, and are defined as the eigenvectors of the moment of inertia tensor of the bone volume. As shown in FIG. 1, principal axes do not capture detailed information regarding the shape, form, localized tangential directions, and curvature of the bone—all of which impact the precision of automated stereological studies of osteological structure and disease assessment. The principal axes primarily indicate the general direction of a bone as a solid object without fully capturing its shape and curvature. Moreover, the principal axes are not useful in characterizing partially circular bones, e.g., the pelvic girdle. As such, they are not useful for automating 2-D slice-by-slice measurements and analysis.
There is a need for automated, precise, and improved methods for stereological analysis and slice-by-slice characterization of bones in images, such as microCT images.